Pedestrian Navigation with INS Measurements and Gait Models

Yan Cui and Kartik B. Ariyur

Abstract:	The accuracy in pedestrian position estimation system is limited if the Global Positioning System (GPS) signal is degraded or blocked. In this paper, an integrated inertial pedestrian navigation system including portable Inertial Measurement Unit (IMU) module and human gait model is presented. The goal of this paper is to fuse the data collected from IMU and estimated stride length from human gait dynamic relationship and bound the inertial drift without GPS signals with Kalman Filter (KF) algorithm applied. Having reviewed several dead reckoning models applied in pedestrian navigation, a KF framework is implemented for sensor fusion. A corrected relationship between stride interval and stride length is developed and integrated for position estimating in long time walking and running tests. Based on the precise stride detection algorithm, our system can bound the inertial estimation error within 5% and even 1% in some certain test. Besides, a methodology with the application of angular rate measured from IMU for distinguishing going upstairs and downstairs from moving in plane is presented as well, to improve the system by working well in three dimensional routes.
Published in:	Proceedings of the 24th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2011) September 20 - 23, 2011 Oregon Convention Center, Portland, Oregon Portland, OR
Pages:	1409 - 1418
Cite this article:	Cui, Yan, Ariyur, Kartik B., "Pedestrian Navigation with INS Measurements and Gait Models," Proceedings of the 24th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2011), Portland, OR, September 2011, pp. 1409-1418.
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